© 1998 by Biometrika Trust
Forensic identification with imperfect evidence
Department of Statistics Science, University College London Gower Street, London WC1E, 6BT, U.K.dawid{at}stats.ucl.ac.uk
Department of Economia, Università di Roma Tre Via Ostiense 139, 00154 Rome, Italymortera{at}uniroma3.it
We study the problem of forensic identification when the trace evidence from the scene of the crime is imperfect: for example, it might be measured with error, or be partially missing. A general framework for imperfect data is developed, and applied in particular to the following cases, singly and in combination: measurement error in the recorded information at the scene of the crime; binning, i.e. discretisation of an originally continuous crime measurement; paternity testing, in which the DNA profiles of the child and of the mother provide partial information on the true father's DNA; two types of laboratory error, one in which the error is equally distributed among all possible results, and a second in which there is a bias in the error mechanism producing a false match; and partial data, as when there is information on the offender's DNA profile, but not on his racial group.
Key Words: Bayes's rule DNA profile Forensic identification Incomplete evidence Match-binning Paternity testing Weight of evidence